Abstract Data Envelopment Analysis (DEA) is a method for measuring efficiencies of Decision Making Units (DMUs). While it has been widely used in many industrial and economic applications, for large DMUs with many inputs and outputs, DEA would require huge computer resources in terms of memory and CPU time. Several studies have attempted to overcome this problem for large datasets. However, the...

Thermo-responsive polymer "nanogels" (crosslinked hydrogel particles with sub-100 nm diameters) are intriguing for many potential applications in biotechnology and medicine. There have been relatively few reports of electrostatically neutral, thermosensitive nanogels comprising a high fraction of hydrophilic co-monomer. Here we demonstrate the syntheses and characterization of novel, non-ionic ...

one of the most popular approaches to measuring productivity changes is based on using malmquist productivity indexes. in this paper we propose a method for obtaining interval malmquist productivity index (impi). the classical dea models have been before used for measuring the malmquist productivity index. the current article extends dea models for measuring the interval malmquist productivity ...

In many organizations and financial institutions, we don't always have acsses to inputs and outputs to evaluate the decision-making units (DMUs), but rather only a ratio of inputs to outputs ( or reverse) might be available. In DEA, cost efficiency determines input standards based on input costs. In multi-stage network DEA processes, in addition to input standards, cost efficiency would determi...

ROBERT CAMPBELL, in honour of whose nmemory this lecture is held, was one of the great pioneers of aseptic surgery. He was the first surgeon to use rubber gloves in the British Isles, and he was responsible for many advances in our craft. He had a particular interest in the surgery of repair, and his appointment at the Children's Hospital gave him nmany opportunities to restore by means of repa...

This article compares two techniques: Data Envelopment Analysis (DEA) and Factor Analysis (FA) to aggregate multiple inputs and outputs in the evaluation of decision making units (DMU). Dِata envelopment analysis (DEA), a popular linear programming technique, is useful to rate comparatively operational efficiency of DMUs based on their deterministic or stochastic input–output data. Factor analys...

Data envelopment analysis (DEA) is used here to determine the relative eciency of 24 top ranked US MBA programs. Eciency scores were determined using three output sets of the MBA programs: output that measured student satisfaction, output that measured recruiter satisfaction and output that measured both. DEA is also used here to determine the relative eciency of three foreign MBA programs a...

This paper studies the effects of heteroscedasticity on the following five types of estimators: (1) Data Envelopment Analysis (DEA) per se as well as DEA joined to regression forms, (2) Corrected Ordinary Least Squares based on maximum residual (COLS-R), (3) Corrected Ordinary Least Squares based on moments of residuals (COLS-M), (4) Maximum Likelihood Estimation (MLE), and (5) Goal Programming...

Data envelopment analysis (DEA) is an effective method to evaluate the relative efficiency of decision-making units (DMUs). In one hand, the DEA models need accurate inputs and outputs data. On the other hand, in many situations, inputs and outputs are volatile and complex so that they are difficult to measure in an accurate way. The conflict leads to the researches of uncertain DEA models. Thi...